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Reda Mastouri
Data scientist proficient in statistics, machine learning, and software engineering. Comfortable with R, python, SQL, and C++ using functional programming and object-oriented design. Examples of my work include machine learning models to optimize sales and marketing programs with an estimated impact of $1 million net revenue annually at a financial institution; I have also built/maintained models to detect risky behavior across millions of third-party sellers on amazon.com. Outside of work, I enjoy distance running, reading, and developing/implementing algorithms in Python.
Industry Experience
Data Scientist
Amazon
Carteret, NJ
Current - 2017
- Build machine learning models to detect Amazon seller fraud activity
- Manage ETL pipelines to enable automated work-flows
- Maintain model efficacy through retraining and error analysis
- Create software tools to monitor machine learning models in production
AVP, Lead Data Scientist
Nuveen
Chicago, IL
2020 - 2017
- Pioneered end-to-end (execution and experimental design) deep learning time series model for client onboarding; estimated impact of the model was $1 million net revenue annually that maximized client journey (improvement in client retention, client growth, etc.)
- Built recommendation engine for 150,000 clients in 50+ products
- Presented model/analysis to executive management; results included model adoption by 100+ sales people and a significant increase sales for clients treated by the model
- Conceptualized and created simulation engine that isolated, detected and measured the ROI impact of company sales events
Senior Equity Research Associate, Financial Services
Raymond James Financial, Inc.
Chicago, IL
2017 - 2014
- Built company and industry models using finance and statistical techniques, including regression and discounted cash flows (DCF)
Education
PhD in Decision Networks & Artificial Intelligence
ENSIAS, Ecole Normale Superieur de l'Enseignement Technique
Rabat, Morocco
Current - 2021
- C++ data structure & algorithms, object-oriented design and programming, systems programming, and software planning and development
MSc. in Data Sciences
Saint Peter's University
Jersey City, NJ
2021
- Coursework in statistics, linear algebra, machine learning, and deep learning
B.S. in Computer Sciences
New Jersey Institute of Technology
Newark, NJ
2020
- C/C++ Data structures & algorithms, object-oriented design and programming
B.A. in Mathematics
Rutgers University
Newark, NJ
2019
Selected Code Repositories
Machine learning decision tree and data frame implementation in C++
Github
Seattle, WA
2021
- Authored with John Nguyen
Generative adversarial network used to generate musical samples
University of Chicago
Chicago, IL
2020
- Capstone project and paper authored with Terry Wang and Rima Mittal. Supervised by Yuri Balasanov
In my free time, I enjoy working with friends, peers, and colleagues on algorithm designs/implementations. Recently, we built data frame and decision tree classes in C++.
Teaching Experience
I am passionate about teaching and helping others. It brings me joy and satisfication to teach others new skills.
Data Understanding via SQL, Databases, and R
University of Chicago
Remote
Current - 2020
- TA and lecture
- Topics include introduction to databases, mySQL, and R
MastersTrack Statistics for Machine Learning
University of Chicago
Coursera
Current - 2020
- TA and lecture
- Topics include simple and multiple regression, logistic regression, hypothesis testing, variable transformations
MastersTrack Machine Learning
University of Chicago
Coursera
Current - 2020
- TA
- Topics include a survey of machine learning algorithms: kNN, support vector machine, decision tree, random forest, boosted trees, and clustering algorithms